Statistical Identification in Svars - Monte Carlo Experiments and a Comparative Assessment of the Role of Economic Uncertainties for the US Business Cycle

CEGE Discussion Paper 375- July 2019

42 Pages Posted: 12 Jul 2019

See all articles by Helmut Herwartz

Helmut Herwartz

University of Goettingen (Gottingen)

Alexander Lange

University of Goettingen (Gottingen)

Simone Maxand

University of Helsinki - Department of Political and Economic Studies

Date Written: July 11, 2019

Abstract

Structural vector autoregressive analysis aims to trace the contemporaneous linkages among (macroeconomic) variables back to underlying orthogonal structural shocks. In homoskedastic Gaussian models the identification of these linkages deserves external and typically notdata-based information. Statistical data characteristics (e.g, heteroskedasticity or non-Gaussian independent components) allow for unique identification. Studying distinct covariance changes and distributional frameworks, we compare alternative data-driven identification procedures and identification by means of sign restrictions. The application of sign restrictions results in estimation biases as a reflection of censored sampling from a space of covariance decompositions. Statistical identification schemes are robust under distinct data structures to some extent. The detection of independent components appears most flexible unless the underlying shocks are (close to) Gaussianity. For analyzing linkages among the US business cycle and distinct sources of uncertainty we benefit from simulation-based evidence to point at two most suitable identification schemes. We detect a unidirectional effect of financial uncertainty on real economic activity and mutual causality between macroeconomic uncertainty and business cycles.

Keywords: independent components, heteroskedasticity, model selection, non-Gaussianity, structural shocks

JEL Classification: C32, E00, E32, E44, G01

Suggested Citation

Herwartz, Helmut and Lange, Alexander and Maxand, Simone, Statistical Identification in Svars - Monte Carlo Experiments and a Comparative Assessment of the Role of Economic Uncertainties for the US Business Cycle (July 11, 2019). CEGE Discussion Paper 375- July 2019. Available at SSRN: https://ssrn.com/abstract=3418405 or http://dx.doi.org/10.2139/ssrn.3418405

Helmut Herwartz

University of Goettingen (Gottingen) ( email )

Platz der Gottinger Sieben 3
Gottingen, D-37073
Germany

Alexander Lange (Contact Author)

University of Goettingen (Gottingen) ( email )

Platz der Gottinger Sieben 3
Gottingen, D-37073
Germany

Simone Maxand

University of Helsinki - Department of Political and Economic Studies ( email )

P.O. Box 54
FIN-00014 Helsinki
Finland

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